• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.571-573
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• 2021

Recently, according to the rapid development of the Internet, information is increasing exponentially. A lot of this information Various studies are being conducted in order to communicate smoothly. In recent years, related researches applying artificial intelligence and big data technologies have been actively conducted. However, it has not produced remarkable results. One of the causes can be found in the severe limitation of the lack of language and knowledge standards. Currently, there is an active research on conferences using a multimedia approach, and gradually, interest in knowledge-based conference systems has begun. In the case of a meeting with a multimedia approach, the advantages and disadvantages of the existing offline meetings are expressed online as they are, and the management of information on the actual contents and process of important meetings is neglected. Therefore, in this paper, we study a plan to convert conference content information into an ontology, and propose a method to systematically analyze the ontology-formed information.

• Science of Emotion and Sensibility
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• v.7 no.4
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• pp.57-65
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• 2004

In this paper, we present a hybrid approach which incorporates color, texture and shape in content-based image retrieval. Colors in each image are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the image. A similarity measure similar to the cumulative color histogram distance measure is defined for this descriptor. The co-occurrence matrix as a statistical method is used for texture analysis. An optimal set of five statistical functions are extracted from the co-occurrence matrix of each image, in order to render the feature vector for eachimage maximally informative. The edge information captured within edge histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features where thus extracted and stored within feature vectors and were later compared with an intersection-based method. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.169-176
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• 2012

This paper presents a parallel object-oriented programming (OOP) platform for efficient visualization of three-dimensional content in CUDA environments. For this purpose, this paper discusses the features and limitations in implementing C++ object-oriented codes using CUDA and proposes the solutions. Also, it presents how to implement a 3D parallel visualization platform based on the MVC (Model/View/Controller) design pattern. Also, it provides sample implementations for integral MLS (iMLS) and signed distance fields (SDFs) based on the Marching Cubes and Raytracing. The proposed approach enables GPU parallel processing only by implementing simple interfaces. Based on this, developers can expect general benefits that are common in general OOP techniques including abstractization and inheritance. Though I implemented only two specific samples in this paper, I expect my approach can be widely applied to general computer graphics problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.2
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• pp.74-80
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• 2013

In this study, a novel and flexible recommender system was developed, based on product taxonomy and usage patterns of users. The proposed system consists of the following four steps : (i) estimation of the product-preference matrix, (ii) construction of the product-preference matrix, (iii) estimation of the popularity and similarity levels for sought-after products, and (iv) recommendation of a products for the user. The product-preference matrix for each user is estimated through a linear combination of clicks, basket placements, and purchase statuses. Then the preference matrix of a particular genre is constructed by computing the ratios of the number of clicks, basket placements, and purchases of a product with respect to the total. The popularity and similarity levels of a user's clicked product are estimated with an entropy index. Based on this information, collaborative and content-based filtering is used to recommend a product to the user. To assess the effectiveness of the proposed approach, an empirical study was conducted by constructing an experimental e-commerce site. Our results clearly showed that the proposed hybrid method is superior to conventional methods.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.3
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• pp.97-117
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• 2013

This study aimed to explore group members' collaborative information by analyzing the number and the content of text contributions on the online discussion board in the group-based research project. This study explored graduate students' collaborative information behavior, affective approach, and types of collaboration and support needed in the group-based research project based on Kuhlthau's Information Search Process(ISP) Model and Yue and He's Collaborative Information Behavior(CIB) Model. It is expected that the results of this study will be useful for understanding of CIB in the group-based research project and applying information literacy instruction to information user in collaboration.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.313-329
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• 2014

This study aims to provide intellectual access to TV content using faceted classification. In order to describe the content of news and current affairs programs, a faceted approach was explored. Based on the Ranganathan's PMEST formula, the basic facets - 'who', 'what', 'how', 'where', 'when' - and their sub-facets were created, specifically for describing the news genre. Additionally, the formal structure and the contextual features of the news genre were mainly considered for creating sub-facets. These created facets were applied to a news genre program. The result shows that these suggested facets are useful for representing well the contextual components of the news genre. The application of faceted classification is expected to improve the identification of the specific TV content.

• Journal of Microbiology and Biotechnology
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• v.34 no.9
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• pp.1912-1918
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• 2024

Single-cell protein (SCP) derived from microorganisms is widely recognized as a viable alternative protein source for the future. Nevertheless, the commercialization of yeast-based SCP is hampered by its relatively low protein content. Therefore, this study aimed to enhance the protein content of Saccharomyces cerevisiae via random mutagenesis. To achieve this, S. cerevisiae KCCM 51811, which exhibited the highest protein concentration among 20 edible S. cerevisiae strains, was selected as a chassis strain. Subsequently, a KCCM 51811 mutant library was constructed (through UV irradiation) and screened to isolate mutants exhibiting high protein content and/or concentration. Among the 174 mutant strains studied, the #126 mutant exhibited a remarkable 43% and 36% higher protein content and concentration, respectively, compared to the parental strain. Finally, the #126 mutant was cultured in a fed-batch system using molasses and corn-steep liquor, resulting in a protein concentration of 21.6 g/l in 100 h, which was 18% higher than that produced by the parental strain. These findings underscore the potential of our approach for the cost-effective production of food-grade SCP.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3111-3111
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• 2001

The implementation of NIR and chemometrics in the Pharmaceutical industries is still in strong progress, both regarding qualitative and quantitative applications and beneficial results are seen. Looking at the development so far, NIR will change the pharmaceutical industry even more in the future. This presentation will address the experiences and progress achieved regarding the application and implementation of quantitative methods for determination of content uniformity and assay of tablets with less than 10% w/w of active, using Near Infrared transmittance spectroscopy in combination with PLS. Also qualitative methods for identification of the same tablets by Near Infrared reflectance spectroscopy will be discussed. Four commercial tablet strengths are formulated and produced from two different compositions by direct compression. Three different strengths are dose proportional, i.e. fixed concentration by varying in size. The aim was to replace the conventional primary methods for analysing content uniformity, assay and identification by NIR. Studies were performed on comparing transmittance versus reflectance spectroscopy for both applications on the dose proportional tablets. The model for determination of content uniformity and assay was developed to cover both coated and uncoated tablets, whereas the qualitative model was developed to identify coated tablets only. The impact of the tablet formulation, tablet size and coating, resulted in individual models far each composition The best calibration was achieved using diffuse reflectance for the identification purposes and diffuse transmittance for the quantitative determination of the active content within the tablets. As NIR in combination with other techniques opens up the possibility of total quality management within the production, the transfer of the above-mentioned models from a laboratory based approach to an at-line approach at H.Lundbeck will be addressed too.